Bacterial meningitis is a severe bacterial infection of the protective brain membranes and can become fatal in as early as 24 hours after symptoms are noticed. According to the World Health Organization, one million cases of bacterial meningitis are estimated to occur and 200,000 of these die annually. However, current approaches for meningitis diagnosis are either costly and time consuming (e.g. cell culture, which may take more than 48 hours.), or need expensive specialized equipment available only in laboratories (e.g. thermal cyclers needed for real-time PCR). All these factors limit the applications of those approaches in resource-limited settings. Considering that many cases of meningitis cases happened in rural high-poverty areas, and the high fatality rate of meningitis, a simple, low-cost, highly-sensitive device and method are greatly needed for immediate and early diagnosis of meningitis in resource-poor settings. The goal of this proposal is to develop a low-cost point of care (POC) device for rapid and highly-sensitive diagnosis of three different types of bacterial meningitis, namely Neisseria meningitidis, Haemophilus influenzae, and Streptococcus pneumonia especially for resource-poor settings. DNA codes with different DNA sequences to target these pathogens will be grafted to paper by utilizing the interaction between the nanomaterial graphene oxide (GO) and single strand DNA. Multiple capture zones on microfluidic devices allow for the detection of these three different species of bacteria on chip simultaneously and specifically, based on DNA hybridization with specific DNA capture probes. A miniaturized film heater will be devised to integrate the loop-mediated isothermal amplification (LAMP) on chip, providing high detection sensitivity. In addition, we also aim to design and perfect an instrument-free, paper-based device for multiplex meningitis diagnosis in field. This project will provide a low-cost paper-based microfluidic POC device and method for immediate and early diagnosis of meningitis especially in resource-poor settings. It will also have great potential in the detection of various plant, animal, foodborne, and infectious diseases from other microorganisms.